Update app.py

app.py

@@ -4,6 +4,43 @@ import gradio as gr
 import re
 import sys
 import shutil
+import importlib.util
+
+def check_requirements():
+    """Check if all required packages are installed and return status"""
+    requirements_status = []
+    
+    packages = [
+        ('gradio', 'gradio'),
+        ('yt-dlp', 'yt_dlp'),
+        ('openai-whisper', 'whisper'),
+        ('torch', 'torch'),
+        ('torchaudio', 'torchaudio'),
+        ('numpy', 'numpy'),
+        ('regex', 'regex'),
+    ]
+    
+    for package_name, import_name in packages:
+        try:
+            spec = importlib.util.find_spec(import_name)
+            if spec is None:
+                requirements_status.append(f"❌ {package_name}: Not found")
+                continue
+            
+            module = importlib.import_module(import_name)
+            version = getattr(module, '__version__', 'Unknown version')
+            requirements_status.append(f"✅ {package_name}: {version}")
+            
+        except ImportError as e:
+            requirements_status.append(f"❌ {package_name}: Import error - {str(e)}")
+        except Exception as e:
+            requirements_status.append(f"⚠️  {package_name}: Found but error - {str(e)}")
+    
+    # Add Python info
+    requirements_status.append(f"\n🐍 Python: {sys.version}")
+    requirements_status.append(f"📁 Python executable: {sys.executable}")
+    
+    return "\n".join(requirements_status)
 
 # Try to import required packages with error handling
 try:
@@ -13,16 +50,44 @@ except ImportError as e:
     YT_DLP_AVAILABLE = False
     print(f"yt-dlp import error: {e}")
 
+# Try multiple whisper import methods
+WHISPER_AVAILABLE = False
+WHISPER_TYPE = None
+
 try:
     import whisper
     WHISPER_AVAILABLE = True
+    WHISPER_TYPE = "openai-whisper"
+    print("Using OpenAI Whisper")
 except ImportError as e:
-    WHISPER_AVAILABLE = False
-    print(f"whisper import error: {e}")
+    print(f"OpenAI Whisper import error: {e}")
+    try:
+        from transformers import pipeline
+        WHISPER_AVAILABLE = True
+        WHISPER_TYPE = "transformers"
+        print("Using Transformers Whisper")
+    except ImportError as e2:
+        print(f"Transformers Whisper import error: {e2}")
 
 print(f"Python version: {sys.version}")
+print(f"Python executable: {sys.executable}")
 print(f"yt-dlp available: {YT_DLP_AVAILABLE}")
-print(f"whisper available: {WHISPER_AVAILABLE}")
+print(f"whisper available: {WHISPER_AVAILABLE} (type: {WHISPER_TYPE})")
+
+# Additional diagnostics
+if YT_DLP_AVAILABLE:
+    try:
+        from yt_dlp import YoutubeDL
+        print(f"yt-dlp version: {YoutubeDL().__class__.__module__}")
+    except:
+        pass
+
+if WHISPER_AVAILABLE and WHISPER_TYPE == "openai-whisper":
+    try:
+        import whisper
+        print(f"whisper version: {whisper.__version__}")
+    except:
+        pass
 
 def download_audio(url, cookies_file_path=None):
     """Download audio from YouTube URL and return the file path"""
@@ -64,16 +129,29 @@ def download_audio(url, cookies_file_path=None):
 def transcribe_audio(file_path):
     """Transcribe audio file using Whisper"""
     if not WHISPER_AVAILABLE:
-        raise Exception("OpenAI Whisper is not available. Please check the installation.")
+        raise Exception("OpenAI Whisper is not available. Please install it using: pip install openai-whisper")
     
     try:
-        # Use the smallest model to reduce memory usage
-        model = whisper.load_model("tiny")
-        result = model.transcribe(file_path)
-        return result["text"]
+        if WHISPER_TYPE == "openai-whisper":
+            # Use OpenAI Whisper
+            model = whisper.load_model("tiny")
+            result = model.transcribe(file_path)
+            return result["text"]
+        
+        elif WHISPER_TYPE == "transformers":
+            # Use Transformers Whisper
+            from transformers import pipeline
+            transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")
+            result = transcriber(file_path)
+            return result["text"]
+        
+        else:
+            raise Exception("No compatible Whisper installation found")
+            
     except Exception as e:
         raise Exception(f"Failed to transcribe audio: {str(e)}")
 
+
 def extract_stock_info_simple(text):
     """Extract stock information using simple pattern matching"""
     try:
@@ -168,10 +246,10 @@ def process_video(url, cookies_file, progress=gr.Progress()):
     
     # Check if required packages are available
     if not YT_DLP_AVAILABLE:
-        return "Error: yt-dlp is not installed properly. Please check the requirements.", "", "❌ Error: Missing yt-dlp"
+        return "Error: yt-dlp is not installed properly. Please install it using: pip install yt-dlp", "", "❌ Error: Missing yt-dlp"
     
     if not WHISPER_AVAILABLE:
-        return "Error: OpenAI Whisper is not installed properly. Please check the requirements.", "", "❌ Error: Missing Whisper"
+        return "Error: OpenAI Whisper is not installed properly. Please install it using: pip install openai-whisper", "", "❌ Error: Missing Whisper"
     
     if not url or not url.strip():
         return "Please provide a valid YouTube URL", "", "❌ Error: Invalid URL"
@@ -251,6 +329,21 @@ with gr.Blocks(
     
     with gr.Row():
         with gr.Column(scale=1):
+            # Requirements check button
+            gr.Markdown("### 🔍 System Check")
+            check_req_btn = gr.Button(
+                "Check Requirements", 
+                variant="secondary",
+                size="sm"
+            )
+            
+            requirements_output = gr.Textbox(
+                label="📋 Requirements Status",
+                lines=10,
+                interactive=False,
+                visible=False
+            )
+            
             # Cookies file upload
             cookies_input = gr.File(
                 label="🍪 Upload Cookies File (cookies.txt)",
@@ -311,6 +404,15 @@ with gr.Blocks(
             )
     
     # Event handlers
+    def show_requirements():
+        status = check_requirements()
+        return gr.update(value=status, visible=True)
+    
+    check_req_btn.click(
+        fn=show_requirements,
+        outputs=[requirements_output]
+    )
+    
     process_btn.click(
         fn=process_video,
         inputs=[url_input, cookies_input],
@@ -329,7 +431,41 @@ with gr.Blocks(
     )
     
     gr.Markdown("""
-    ### 🔧 Troubleshooting:
+    ### 🔧 Installation & Troubleshooting:
+    
+    **Step 1: Click "Check Requirements" button above to see what's missing**
+    
+    **If you get "Whisper Missing" error:**
+    ```bash
+    pip install openai-whisper
+    ```
+    
+    **If you get "yt-dlp Missing" error:**
+    ```bash
+    pip install yt-dlp
+    ```
+    
+    **Install all requirements at once:**
+    ```bash
+    pip install gradio==4.44.0 yt-dlp==2023.12.30 openai-whisper==20231117 torch==2.1.0 torchaudio==2.1.0 numpy==1.24.3 regex==2023.8.8
+    ```
+    
+    **Alternative Whisper installation:**
+    ```bash
+    pip install transformers torch torchaudio
+    ```
+    
+    **If using virtual environment:**
+    ```bash
+    # Create and activate virtual environment first
+    python -m venv myenv
+    # Windows: myenv\\Scripts\\activate
+    # Mac/Linux: source myenv/bin/activate
+    # Then install packages
+    pip install -r requirements.txt
+    ```
+    
+    **Other Issues:**
     - **Bot Detection Error**: Upload your cookies.txt file
     - **No Audio Found**: Check if video has audio track
     - **Transcription Failed**: Video might be too long or audio quality poor